Conditional independence graph for nonlinear time series and its application to international financial markets

Conditional independence graphs are proposed for describing the dependence structure of multivariate nonlinear time series, which extend the graphical modeling approach based on partial correlation. The vertexes represent the components of a multivariate time series and edges denote direct dependence between corresponding series. The conditional independence relations between component series are tested efficiently and consistently using conditional mutual information statistics and a bootstrap procedure. Furthermore, a method combining information theory with surrogate data is applied to test the linearity of the conditional dependence. The efficiency of the methods is approved through simulation time series with different linear and nonlinear dependence relations. Finally, we show how the method can be applied to international financial markets to investigate the nonlinear independence structure.     

Parameter dependence and outcome dependence in dynamical models for state vector reduction

We apply the distinction between parameter independence and outcome independence to the linear and nonlinear models of a recent nonrelativistic theory of continuous state vector reduction. We show that in the nonlinear model there is a set of realizations of the stochastic process that drives the state vector reduction for which parameter independence is violated for parallel spin components in the EPR-Bohm setup. Such a set has an appreciable probability of occurrence ( 1/2). On the other hand, the linear model exhibits only extremely small parameter dependence effects. We investigate some specific features of the models and we recall that, as has been pointed out recently, if one wants to be able to speak of definite outcomes (or equivalently of possessed objective elements of reality) at finite times, one has to slightly change the criteria for their attribution to physical systems. The concluding section is devoted to a detailed discussion of the difficulties which one meets when one tries to take, as a starting point for the formulation of a relativistic theory, a nonrelativistic scheme which exhibits parameter dependence. Here we derive a theorem which identifies the precise sense in which the occurrence of parameter dependence forbids a genuinely relativistic generalization. Finally we show how the appreciable parameter dependence of the nonlinear model gives rise to problems with relativity, while the extremely weak parameter dependence of the linear model does not give rise to any difficulty, provided one takes into account the appropriate criteria for the attribution of definite outcomes.Work supported in part by the Trieste Section of the INFN.     

Parameter dependence in dynamical models for statevector reduction

We apply the distinction between parameter independence and outcome independence to the linear and nonlinear models of a recent nonrelativistic theory of continuous statevector reduction. We show that in the nonlinear model there is a set of realizations of the stochastic process that drives the statevector reduction for which parameter independence is violated for parallel spin components in the EPR-Bohm setup. Such a set has an appreciable probability of occurrence ( 1/2). On the other hand, the linear model exhibits only extremely small parameter dependence effects. The final section discusses the difficulties of finding a relativistic generalization of a parameter-dependent nonrelativistic theory. We identify this difficulty precisely and show how the weak parameter dependence of the linear model avoids it, provided one uses an appropriate criterion for the existence of definite outcomes.     

Nuclear symmetry energy effects in finite nuclei and neutron star

Within a relativistic mean-field model with nonlinear isoscalar–isovector coupling, we explore the possibility of constraining the density dependence of nuclear symmetry energy from a systematic study of the neutron skin thickness of finite nuclei and neutron star properties. We find the present skin data supports a rather stiff symmetry energy at subsaturation densities that corresponds to a soft symmetry energy at supranormal densities. Correlation between the skin of ²⁰⁸Pb and the neutron star masses and radii with kaon condensation has been studied. We find that ²⁰⁸Pb skin estimate suggest star radii that reveals considerable model dependence. Thus precise measurements of neutron star radii in conjunction with skin thickness of heavy nuclei could provide significant constraint on the density dependence of symmetry energy.     

The Role of Instrumental Variables in Causal Inference Based on Independence of Cause and Mechanism

Causal inference methods based on conditional independence construct Markov equivalent graphs and cannot be applied to bivariate cases. The approaches based on independence of cause and mechanism state, on the contrary, that causal discovery can be inferred for two observations. In our contribution, we pose a challenge to reconcile these two research directions. We study the role of latent variables such as latent instrumental variables and hidden common causes in the causal graphical structures. We show that methods based on the independence of cause and mechanism indirectly contain traces of the existence of the hidden instrumental variables. We derive a novel algorithm to infer causal relationships between two variables, and we validate the proposed method on simulated data and on a benchmark of cause-effect pairs. We illustrate by our experiments that the proposed approach is simple and extremely competitive in terms of empirical accuracy compared to the state-of-the-art methods.     

Correlation-anti-correlation transition by state-dependent Poisson noise

Noise may induce some degrees of order in many biological and complex systems. We present an example of a noise-dependent transition from correlation to anti-correlation of the states of a bivariate system coupled by state-dependent Poisson noises. By varying the degree of dependence of the rate of jumps on the other variable, the system undergoes different degrees of correlation, from independence to perfect correlation (which in this case coincides with perfect synchronization) in the limit of the deterministic, periodic case.     

Using permutations to detect dependence between time series

In this paper, we propose an independence test between two time series which is based on permutations. The proposed test can be carried out by means of different common statistics such as Pearson’s chi-square or the likelihood ratio. We also point out why an exact test is necessary. Simulated and real data (return exchange rates between several currencies) reveal the capacity of this test to detect linear and nonlinear dependences.     

Graph cohomology classes in the Batalin–Vilkovisky formalism

This paper gives a conceptual formulation of Kontsevich’s ‘dual construction’ producing graph cohomology classes from a differential graded Frobenius algebra with an odd scalar product. Our construction–whilst equivalent to the original one–is combinatorics-free and is based on the Batalin–Vilkovisky formalism, from which its gauge independence is immediate.     

Carrier-mediated ferromagnetism in N co-doped (Zn, Mn)O-based diluted magnetic semiconductors

Mn-doped ZnO is anti-ferromagnetic spin glass state, however, it becomes half-metallic ferromagnets upon hole doping. In this Letter we report a theoretical study of (Zn, Mn)O system codoped with N, and show that this codoping can change the ground state from anti-ferromagnetic to ferromagnetic. We have carried out the first-principles electronic structure calculations and report total energy to estimate whether the ferromagnetic state was stable or not. Our approach is based on the spin-polarized relativistic Korringa–Kohn–Rostoker (SPR–KKR) density functional theoretical (DFT) method, within the coherent potential approximation (CPA). Self-consistent electronic structure calculations were performed within the local density approximation, using the Vosko–Wilk–Nusair parameterization of the exchange-correlation energy functional. Our results for energy difference between ferromagnetic sate and spin glass state as well as their dependence on concentrations were presented and discussed.     

Bivariate phase-rectified signal averaging

Phase-Rectified Signal Averaging (PRSA) was shown to be a powerful tool for the study of quasi-periodic oscillations and nonlinear effects in non-stationary signals. Here we present a bivariate PRSA technique for the study of the inter-relationship between two simultaneous data recordings. Its performance is compared with traditional cross-correlation analysis, which, however, does not work well for non-stationary data and cannot distinguish the coupling directions in complex nonlinear situations. We show that bivariate PRSA allows the analysis of events in one signal when the other signal is in a certain phase or state; it is stable in the presence of noise and impassible to non-stationarities.     

Detecting positive feedback in multivariate time series: The case of metal prices and US inflation

The objective of this paper is to examine causality and feedback relationships between primary commodity prices and US inflation. To this end, the bivariate noisy Mackey–Glass process recently developed by Kyrtsou and Labys [Evidence for chaotic dependence between US inflation and commodity prices, J. Macroecon. 28(1) (2006) 256–266] has been applied to assess this relationship. Results obtained support evidence in favour of causality, which can help to identify the influences of speculative price behaviour on inflation.     

Neutron–proton elliptic flow difference as a probe for the high density dependence of the symmetry energy

We employ an isospin dependent version of the QMD transport model to study the influence of the isospin dependent part of the nuclear matter equation of state and in-medium nucleon–nucleon cross-sections on the dynamics of heavy-ion collisions at intermediate energies. We find that the extraction of useful information on the isospin-dependent part of the equation of state of nuclear matter from proton or neutron elliptic flows is obstructed by their sensitivity to model parameters and in-medium values of nucleon–nucleon cross-sections. Opposite to that, neutron–proton elliptic flow difference shows little dependence on those variables while its dependence on the isospin asymmetric EoS is enhanced, making it more suitable for a model independent constraining of the high-density behaviour of asy-EoS. Comparison with existing experimental FOPI-LAND neutron–hydrogen data can be used to set an upper limit to the softness of asy-EoS. Successful constraining of the asy-EoS via neutron–proton elliptic flow difference will require experimental data of higher accuracy than presently available.     

Improving Clapper–Yule model of the reflectance prediction by the path branching factor depending on the screen frequency of color halftone imaging

The new path branching Clapper–Yule prediction model of spectral reflectance based on the traveling probability and the path branching factor depending on the characteristic parameter of paper and spatial distribution of imaging dots is proposed. Our numerical results show that the new spectral reflectance model is more close to the experimental data than the basic Clapper–Yule model and the reflectance is a nonlinear function of the dot percentage coverage of the halftone imaging.     

Independent Component Analysis to enhance performances of Karhunen–Loeve expansions for non-Gaussian stochastic processes: Application to uncertain systems

In the context of engineering systems, an essential step in uncertainty quantification is the development of accurate and efficient representation of the random input parameters. For such input parameters modeled as stochastic processes, Karhunen–Loeve expansion is a classical approach providing efficient representations using a set of uncorrelated, but generally statistically dependent random variables. The dependence structure among these random variables may be difficult to estimate statistically and is thus ignored in many practical applications. This simplifying assumption of independence may lead to considerable errors in estimating the variability in the system state, thus limiting the effectiveness of Karhunen–Loeve expansion in certain cases. In this paper, Independent Component Analysis is exploited to linearly transform the random variables used in Karhunen–Loeve expansion resulting into a set of random variables exhibiting higher order decorrelation. The stochastic wave equation is investigated for numerical illustration whereby the random stiffness coefficient is modeled as a non-Gaussian stochastic process. Under the assumption of independence among the random variables used in the Karhunen–Loeve expansion and Independent Component Analysis representations, the latter provides more accurate statistical characterization of the output process for the specific cases examined.     

Spin correlations in nonperturbative electron–positron pair creation by petawatt laser pulses colliding with a TeV proton beam

The influence of the electron spin degree of freedom on nonperturbative electron–positron pair production by high-energy proton impact on an intense laser field of circular polarization is analyzed. Predictions from the Dirac and Klein–Gordon theories are compared and a spin-resolved calculation is performed. We show that the various spin configurations possess very different production probabilities and discuss the transfer of helicity in this highly nonlinear process. Our predictions could be tested by combining the few-TeV proton beam at CERN-LHC with an intense laser pulse from a table-top petawatt laser source.     

A light-front coupled-cluster method for the nonperturbative solution of quantum field theories

We propose a new method for the nonperturbative solution of quantum field theories and illustrate its use in the context of a light-front analog to the Greenberg–Schweber model. The method is based on light-front quantization and uses the exponential-operator technique of the many-body coupled-cluster method. The formulation produces an effective Hamiltonian eigenvalue problem in the valence Fock sector of the system of interest, combined with nonlinear integral equations to be solved for the functions that define the effective Hamiltonian. The method avoids the Fock-space truncations usually used in nonperturbative light-front Hamiltonian methods and, therefore, does not suffer from the spectator dependence, Fock-sector dependence, and uncanceled divergences caused by such truncations.     

Numerical simulation of a solitonic gas in KdV and KdV–BBM equations

The collective behaviour of soliton ensembles (i.e. the solitonic gas) is studied using the methods of the direct numerical simulation. Traditionally this problem was addressed in the context of integrable models such as the celebrated KdV equation. We extend this analysis to non-integrable KdV–BBM type models. Some high resolution numerical results are presented in both integrable and nonintegrable cases. Moreover, the free surface elevation probability distribution is shown to be quasi-stationary. Finally, we employ the asymptotic methods along with the Monte Carlo simulations in order to study quantitatively the dependence of some important statistical characteristics (such as the kurtosis and skewness) on the Stokes–Ursell number (which measures the relative importance of nonlinear effects compared to the dispersion) and also on the magnitude of the BBM term.     

XTOR-2F: A fully implicit Newton–Krylov solver applied to nonlinear 3D extended MHD in tokamaks

XTOR-2F solves a set of extended magnetohydrodynamic (MHD) equations in toroidal tokamak geometry. In the original XTOR code, the time stepping is handled by a semi-implicit method 1, 2 and 3. Moderate changes were necessary to transform it into a fully implicit one using the NITSOL library with Newton–Krylov methods of solution for nonlinear system of equations [4]. After addressing the sensitive issue of preconditioning and time step tuning, the performances of the semi-implicit and the implicit methods are compared for the nonlinear simulation of an internal kink mode test case within the framework of resistive MHD including anisotropic thermal transport. A convergence study comparing the semi-implicit and the implicit schemes is presented. Our main conclusion is that on one hand the Newton–Krylov implicit method, when applied to basic one fluid MHD is more computationally costly than the semi-implicit one by a factor 3 for a given numerical accuracy. But on the other hand, the implicit method allows to address challenging issues beyond MHD. By testing the Newton–Krylov method with diamagnetic modifications on the dynamics of the internal kink, some numerical issues, to be addressed further, are emphasized.     

Testing Born-Infeld electrodynamics in waveguides

Waveguides can be employed to test nonlinear effects in electrodynamics. We solve Born-Infeld equations for TE waves in a rectangular waveguide. We show that the energy velocity acquires a dependence on the amplitude, and harmonic components appear as a consequence of the nonlinear behavior.